Maritime target search path planning based on improved ant colony algorithm
Aiming at the problems of slow convergence speed and easy to fall into local optimality in the minimum time search(MTS)path programming problem of the maximum and minimum ant colony system(MMAS)algorithm,an improved algorithm based on MMAS is proposed.Firstly,the heuristic function factor is improved combined with the target motion speed.Secondly,pheromones are rewarded for the optimal path.In addition,updated pheromones are used to meet the normal distributed pheromones with adaptive volatilization coefficients,the improved algorithm can speed up the convergence speed of the algorithm and avoid the search falling into local optimum.Simulation results show that the improved ant colony algorithm has a higher probability of searching the target in the search path,and the expected search time is shorter.
target searchpath planningpheromones tablesheuristic functionnormal distribution
万方数据
维普
